Innovations and Challenges of Artificial Intelligence in Remote Patient Monitoring
SUMMARY:
Remote patient monitoring (RPM) has grown dramatically since the pandemic and is expected to continue.
Artificial intelligence (AI) incorporated into patient monitoring and telemedicine is the next major innovation in this space.
Each new innovation has a number of challenges to be accounted for by anyone evaluating these tools.
REVIEW
The use of RPM has been adopted across various patient groups and setting with expected annual growth rates of 18.9% by 2028.
Although the use of RPM have shown promise in patient engagement and experience, there is inconclusive data on the clinical and financial impact compared to usual care.
Artificial intelligence (AI) incorporation into patient monitoring and telemedicine is increasingly being discussed and harnessed.
Within AI in healthcare, Natural Language Processing (NLP) is being used to interpret the human language to improve patient engagement and telemedicine.
AI advancements are changing the delivery of care via new and innovative instruments.
Although there is great potential value in these tools, there are also large inherent challenges.
Innovations include:
Virtual assistance chatbots
Real time patient monitoring
Predictions of disease progression and risk stratification
Personalized treatment recommendations
Automated scheduling and reminders
Below are the major applications of artificial intelligence in healthcare, the potential value they provide and challenges.
AI into RPM
CONCLUSIONS:
AI within RPM will continue to evolve and grow.
Coupled with natural language processing (NLP) , algorithms will be addressing a number of dynamic issues with the potential for great value.
These profound tools have some significant challenges which developers and users need to be aware of prior to widespread adoption.